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| 基于粗糙集的改进BP神经网络算法研究 | |
| 引用本文： | 张利,吴华玉,卢秀颖.基于粗糙集的改进BP神经网络算法研究[J].大连理工大学学报,2009,49(6):971-976. |
| 作者姓名： | 张利 吴华玉 卢秀颖 |
| 作者单位： | 1. 大连理工大学,电子与信息工程学院,辽宁,大连,116024;辽宁大学,信息科学与技术学院,辽宁,沈阳,110036 2. 上海财经大学,上海,200433 3. 大连理工大学,电子与信息工程学院,辽宁,大连,116024 |
| 基金项目： | 国家自然科学基金资助项目(60573172) |
| 摘 要： | 提出了一种基于粗糙集和遗传算法的改进BP神经网络算法.该算法首先对原始数据集进行属性约简,优化BP神经网络的输入变量;然后利用遗传算法全局搜索的特点,优化BP神经网络初始权重和阈值.将改进BP神经网络算法应用于客户分类,训练误差为5.92×10-12,测试总误差为0.00023;而改进前的一个比较理想的训练结果的训练误差为0.0016,测试总误差为0.073.Matlab仿真表明改进的BP神经网络算法有更好的训练精度和泛化能力. |
| 关 键 词： | BP神经网络 粗糙集 遗传算法 属性约简 |
An improved BP neural network algorithm based on rough set |
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| ZHANG Li,WU Huayu,LU Xiuying.An improved BP neural network algorithm based on rough set[J].Journal of Dalian University of Technology,2009,49(6):971-976. | |
| Authors: | ZHANG Li WU Huayu LU Xiuying |
| Institution: | ZHANG Li1,2,WU Hua-yu3,LU Xiu-ying11.School of Electronic , Information Engineering,Dalian University of Technology,Dalian 116024,China,2.School of Information Science , Technology,Liaoning University,Shenyang 110036,3.Shanghai University of Finance , Economics,Shanghai 200433 |
| Abstract: | An improved BP neural network algorithm is proposed based on rough set and genetic algorithm. Firstly, attribute reduction is carried out on original data sets, and the input variables of the BP neural network are optimized. Then, based on the global searching characteristic of genetic algorithm, the original weight and threshold of the BP neural network are optimized. Finally, the improved BP neural network is applied to the custom classification, the training error is 5. 92×10(~-12), and the total test error is 0. 000 23, while an ideal training result's training error before improvement is 0. 001 6, and the total test error is 0. 073. Through the simulation of Matlab, it indicates that the improved BP neural network algorithm has better training precision and extensive ability. |
| Keywords: | BP neural network rough set genetic algorithm attribute reduction |
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